Search NASA⌕ Search

SEARCH · Search NASA

Results for “Risk Management”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records

Quantitative Risk Management - Risk Informed Decision Making on High-Risk Waste Remediation Projects - 19022

For every $1 billion invested in projects, $97 million is wasted due to poor project performance. That means 9.7% of money spent on projects is wasted due to poor risk and uncertainty management. High-risk projects, similar to those in waste remediation, have the most to lose. A solid quantitative risk management program is one of the keys to increasing the likelihood that a project will succeed. A quantitative risk program solves two major problems that challenge the effective management of risk and uncertainty: 1. Risks arise at all levels of an organization; however, not all organizational levels have an effective way to identify and resolve them. This can lead to risks that, even if identified, are not reported. 2. Decision-makers are often forced to operate solely on intuition when implementing mitigation strategies, not fully understanding the effects that certain decisions have on the program's cost and schedule. A quantitative risk program uses a risk register and builds it into the project/program integrated schedule to assess the impact of these risks, typically at the 80% confidence contingency level for specific milestones and/or project completion. Implementing a quantitative risk program drives a forward-thinking, proactive mentality to problem solving into all levels of the organization. A healthy risk program for regular reporting and communication ensures that all members of an organization are thinking about risks and using their communication channels to resolve them. It gives a method of communication and incentive for all levels in the organization and helps to ensure that risks will be reported and resolved. Pacific Northwest National Laboratory (PNNL) has developed tools and methods that provide a level of realism for analyzing different scenarios and estimating contingency that does not exist in the standard industry risk tool kit. These tools and methods provide decision-makers with actionable, quantitatively based information to guide their decision making. The first tool is a probabilistic branching risk model for mitigation strategies. Current quantitative risk analysis tools in the industry simulate two cases: fully mitigated and un-mitigated. In the fully mitigated case, the user assumes that every planned mitigation activity is successful. In the un-mitigated case, the user assumes that none are successful. The truth lies between these two extremes. The PNNL team has developed a probabilistic risk model for mitigation scenarios that includes a probability that a mitigation activity will succeed and a probability that a mitigation action will be funded. These probabilities are elicited from subject matter experts and ensure that the contingency calculations at the specified confidence are approaching reality. The second tool developed at PNNL is the Risk Box, which is a tool that integrates with different scenarios in the risk register. For example, say the user is faced with two different and mutually exclusive mitigation actions to reduce a risk. The Risk Box methodology performs the contingency calculations and then displays them on a time-phased graph that shows how each scenario reduces the risk contingency needed on the project/program. This graph then provides quantitative information to show decision-makers which mitigation action provides the greatest reduction (cost and schedule) in risk contingency for the program. Implementing these and other tools within a structured risk program increases the likelihood that a project will come in on schedule and budget, ensures that all personnel are proactively thinking about problems and resolutions, creates communication channels for all members to submit and resolve potential problems, produces a prioritized list of risk rankings to focus leadership on issues that may cause the biggest problems, and implements processes that drive updates to the risk program as the risk profile changes. PNNL has been developing these methods and using them on projects for over 20 years. They have been successfully applied on waste management projects, high-tech research and development projects, and construction projects, and they continue to be used on a number of U.S. Department of Energy projects today. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Risk Management and Risk Aversion, from Benefit to Impediment

Risk management is a critical tool for improving the probability of project success by identifying, assessing, prioritizing, and attempting to control threats to project realization. For industries that require high operational reliability due to the potential consequences of off-normal events, such as the nuclear, aerospace, and chemical sectors, a major focus of risk management is the preservation of process safety. Due to the nature of the processes or systems under consideration, the associated process safety analyses (such as risk and safety assessments) and safety features can require significant resources. These costs are typically tolerated either due to the need to satisfy regulatory requirements or based on the assumption that they generally decrease the occurrence of unwanted events and therefore improve the probability of project success. However, as the level of acceptable or tolerable risk from unwanted events decreases, the required resources necessary for ensuring and demonstrating satisfaction of these criteria can grow and in turn can become one of the dominant impediments to project success. This paper outlines a high-level theoretical framework for the consideration of dominant project risks, which includes potential project failure from both the occurrence of high consequence off-normal events and the inability to achieve project completion due to the resource needs and innovation losses associated with extreme risk aversion. Utilizing such an integrated approach permits an attempt to optimize the probability of successful project realization while also providing valuable insight into the proper level of acceptable risk. The work is presented as a first step, in hopes of spurring additional discussion and analysis regarding appropriate levels of risk tolerance and the balance of project benefits.

Grabaskas, David↗

Applying the Risk Management Framework: The Distributed Energy Resource Risk Manager

As part of a multiyear effort, the National Renewable Energy Laboratory (NREL) has dedicated resources to understand and identify cybersecurity weaknesses in distributed energy resources (DERs) by performing assessments. Due to a lack of standardization and rapidly increasing adoption of DERs, there is a critical need to address cybersecurity needs for DER systems in an interactive way. Furthermore, federal agencies, which are required to obtain an authority to operate, are challenged by the complexities of including their DERs. To help meet this need, in early 2020, NREL released the Distributed Energy Resources Cybersecurity Framework (DERCF) and accompanying Web application. This process is supported by the Risk Management Framework (RMF) developed by the National Institute of Standards and Technology. This project, referred to as the DERCF RMF application, expands on the existing DERCF work to include methods that support walking a user through the seven RMF steps. The tool will be available for download at no cost from [link ]. The purpose of this paper is to describe the steps the DERCF team at NREL took to understand Steps 1-5 of the RMF process. Additionally, this document will identify future work on the first five steps as well as a plan for Steps 6 and 7.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Opportunities for Earth Observation to Inform Risk Management for Ocean Tipping Points

Abstract As climate change continues, the likelihood of passing critical thresholds or tipping points increases. Hence, there is a need to advance the science for detecting such thresholds. In this paper, we assess the needs and opportunities for Earth Observation (EO, here understood to refer to satellite observations) to inform society in responding to the risks associated with ten potential large-scale ocean tipping elements: Atlantic Meridional Overturning Circulation; Atlantic Subpolar Gyre; Beaufort Gyre; Arctic halocline; Kuroshio Large Meander; deoxygenation; phytoplankton; zooplankton; higher level ecosystems (including fisheries); and marine biodiversity. We review current scientific understanding and identify specific EO and related modelling needs for each of these tipping elements. We draw out some generic points that apply across several of the elements. These common points include the importance of maintaining long-term, consistent time series; the need to combine EO data consistently with in situ data types (including subsurface), for example through data assimilation; and the need to reduce or work with current mismatches in resolution (in both directions) between climate models and EO datasets. Our analysis shows that developing EO, modelling and prediction systems together, with understanding of the strengths and limitations of each, provides many promising paths towards monitoring and early warning systems for tipping, and towards the development of the next generation of climate models.

Wood, Richard A. (ORCID:0000000239609513)↗

The Distributed Energy Resource Risk Manager

Organizations need a comprehensive approach to managing security and privacy risks, especially for energy resources that are becoming increasingly distributed. A tool by the National Renewable Energy Laboratory (NREL) makes it possible to manage these risks and maintain the highest standards of cybersecurity. To simplify risk management for facilities and distributed energy resources, NREL has created the Distributed Energy Resource Risk Manager, an automated, user-friendly tool that helps navigate and implement one of the most widely trusted frameworks for information security, the National Institute of Standards and Technology Risk Management Framework.

compliance↗

Marine Energy Technology Development Risk Management Framework

Over the past decades, the global marine energy industry has suffered a number of serious technological and commercial setbacks. To help reduce the risks of industry failures and advance the development of new technologies, the U.S. Department of Energy (DOE) and the National Renewable Energy Laboratory (NREL) developed a Marine Energy Risk Management Framework in 2015, with this revision published in 2024. This risk management framework shall be utilized on all DOE Water Power Technologies Office (WPTO) projects that require system testing in the open water. By addressing uncertainties, the Marine Energy Risk Management Framework increases the likelihood of successful development of marine energy converter technology. It covers projects of any technology readiness level technology performance level (TPL) and all risk types (e.g. technological risk, regulatory risk, commercial risk) over the development cycle. This risk framework is not a substitute for other risk management procedures that may be required for marine operations, such as installations at sea, hoisting and rigging, safe diver operations, and other safety requirements. This risk framework is intended to meet DOE's risk management expectations for marine energy technology research and development efforts from WPTO. It also provides an overview of other relevant risk management tools and documentation.

16 TIDAL AND WAVE POWER↗

Automation for Distributed Energy Resources Risk Manager Using OSCAL

The risk management framework (RMF) provides a well-organized and thorough approach to diagnose information technology (IT) system threats, to gather required materials to comply with industry standards, and to document a plan for achieving authority to operate (ATO). ATO is given by the operating authority with the awareness of vulnerabilities that arise when operating the IT system. The primary goal of the National Renewable Energy Laboratory’s (NREL’s) distributed energy resource (DER) RM application is to provide a user-friendly interface and in-depth guidance for generating the authorization package for the authorizing official to review. In other words, the application satisfies steps 1 through 7 of the RMF process with a focus on DERs.

cybersecurity↗

2023 Risk Management Plan and Register for Low-Power WEC for Non-Grid Applications

This is an updated risk management plan and risk register for the design, build and test of a novel, remote, low-power wave energy converter (WEC) for non-grid applications. This Columbia Power Technologies project seeks to develop a prototype low-power WEC that lowers the total cost of ownership and provides robust, new capabilities for customers in the maritime environment. The testing location for this prototype is the U.S. Navy Wave Energy Test Site (WETS) in Kaneohe Bay, O'ahu, Hawai'i. Detailed in the Risk Management Plan document is a Failure Modes, Effects, and Criticality Analysis (FMEC) that systematically identifies all potential failure modes and their effects on the system. Risk registers for major subsystems were completed according to the methodology described in the Risk Management Plan and are also included here.

16 TIDAL AND WAVE POWER↗

Supply Chain Risk Management: Data Structuring

Supply chain risk management (SCRM) is an area of research that addresses both logistics concepts to maximize efficiency, reliability, and revenue as well as risk features, such as potential weak points, break points, and vulnerabilities within the supply chain. SCRM is used to find risks introduced at each node in a supply chain and how these risks can impact a company’s products, individuals, customers, and reputation. SCRM is a relatively new field, so standardized processes including data structuring are not fully documented. This paper explains the importance of a standard data structuring methodology and how it can enhance current SCRM efforts. Data ingest, structuring, and analysis are predominantly managed by humans. Automating some of the less complex steps can positively impact SCRM by allowing human analysts to focus on more strategic analyses. Types of data to be collected and structured are collected via publicly available information related to hardware, software, and corporate entities. After the data has been collected, the information is formatted in a specific manner, conforming to a schema, to allow for more effective and efficient ingest for further analysis. This paper outlines data structures used by Pacific Northwest National Laboratory for SCRM research and analysis purposes. These structures have been used for hundreds of analyses and have been successful in developing a common baseline. Data structuring is one of the first steps in data standardization, which will further mature and enhance the SCRM research area.

supply chain risk management, data structuring, re↗

Cybersecurity assessment and risk management tool

Techniques and apparatuses are described for a cybersecurity risk management tool to assess cybersecurity risk and prioritize cybersecurity correction plans. The cybersecurity risk management tool categorizes cybersecurity framework security controls into maturity indicator levels, identifies implementation states achieved by an entity with respect to the cybersecurity framework security controls, and determines which of the maturity indicator levels represents the implementation state achieved by the entity with respect to each of the cybersecurity framework security controls. A cost-benefit analysis for modifying from the implementation state achieved by the entity to a next implementation state to be achieved by the entity with respect to the cybersecurity framework security controls is also enabled. The cost-benefit analysis leverages factored weights including aspects indicative of security perspectives, Gaussian distributions, and the maturity indicator levels.

Gourisetti, Sri Nikhil Gupta↗

Risk Management for CO 2 Storage Projects

Conference poster presented at American Association of Petroleum Geologists (AAPG) Carbon Capture, Utilization, and Storage (CCUS) Conference, Houston, Texas, April 25–27, 2023. There is no one-size-fits-all risk management approach for storage projects. Instead, risk management is about having a detailed process in place, adhering to that process throughout the project life cycle, and adapting the process depending on site-specific conditions, applicable regulatory requirements, and any additional requirements imposed by pursuing one or more financial incentive programs. The Plains CO 2 Reduction (PCOR) Partnership Initiative experience has demonstrated the value of managing risk analysis in concert with storage project regulatory permit requirements, which drive the geologic exhibits and site characterization needs for the permit and the risk analysis.

01 COAL, LIGNITE, AND PEAT↗

MHK Risk Management Framework

Marine and Hydrokinetic Energy Risk Management Framework presentation from Water Power Technologies Office Peer Review, FY14-FY16.

13 HYDRO ENERGY↗

Risk Management for Ocean-Based Technologies [Slides]

This presentation discusses risk management for ocean-based technologies by stepping through elements of the National Laboratory of the Rockies' 2024 Marine Energy Technology Development Risk Management Framework.

16 TIDAL AND WAVE POWER↗

Obstacles to Practical Digital Supply Chain Risk Management in the Energy Sector

Cyber supply chain risk management (C-SCRM) programs must consider operations that depend on the lifecycles of digital components such as hardware, firmware, software, and services. We integrate academic literature, historical incidents, and existing standards to identify obstacles faced by C-SCRM programs.

Business Process Management & Integration↗

Integrating Cyber-Informed Engineering into Enterprise Risk Management

This document supports the application of Cyber-Informed Engineering (CIE) within the context of Enterprise Risk Management (ERM) to enhance cyber-resilience. It highlights that many critical infrastructure organizations use ERM to manage business risks and emphasizes the importance of evaluating critical systems and assets. The proposed approach can be adopted independently of formal ERM processes and offers a starting point for integrating CIE alongside existing or new ERM practices. Both CIE and ERM are iterative, and their alignment fosters continuous improvement and supports the engineering and operations cultures of an organization.

42 ENGINEERING↗

Risk Management Overview for Small Business [Slides]

Project Risk Management is a formal process of identifying, analyzing, and responding to negative and positive events that may arise during a project or process lifecycle in order to increase the likelihood that project goals are met on time and on budget.

99 GENERAL AND MISCELLANEOUS↗